ISPOR 16th Annual International Congress
A novel approach for Non-Adherence/Non-Persistence measurement based on prescription data: The example of oral diabetics in the therapy of type 2 diabetes mellitus patients
Baltimore MD, USA, 21. bis 25. Mai 2011
Wilke T. (1), Mueller S. (1), Lindner R. (2), Ahrens S. (2 ), Verheyen F. (2)
1University of Wismar, Wismar, Germany; 2 WINEG, Hamburg, Germany
To quantify the influence of methodological assumptions/parameters on the results of prescription-based NA analysis based on 3-years prescription data (German Statutory Health Insurance Fund) covering 241,537 T2DM patients.
With the help of MPRs in an interval-based approach, a NA-base scenario for 25 anti-diabetic active ingredients was calculated for each patient. In a scenario analysis, the quantitative influence of all in all 9 parameters on the MPR level was derived. The most important parameter concerned the definition of an ideal prescription profile (“100%-adherer”). Assumptions simplifying the real prescription behaviour did not allow to accurately reflect the variety of medications and the clinical need to change medications. Therefore, a total of eight clinically meaningful prescription profiles were derived assigning patients exclusively by the use of self-developed algorithms. For each patient a MPR estimated by standard methodology (base case) was compared with the MPR based on our novel approach.
In the base case, the average MPR resulting from the analysed active ingredient combinations was 80.76%. A total of 62.85% of patients had an MPR80%. According to the novel prescription profiles, patients were distributed as follows: 59.9% Mono-medication, 12.9% Single-Drug Switcher, 11.3% Single-Drug Add-on, 2.0% Multiple-Drug Add-on, 5.0% Polytherapy consistent,
2.5% Polytherapy Add-on, 3.5% Polytherapy Drop-off, and 1.3% Polytherapy Switcher. A total of 1.6% of the patients could not unequivocally be assigned to one of the categories. Comparing a base-case MPR analysis with our novel approach resulted in MPR deviations in specific patient groups of up to 27.4 percentage points.
Probably the biggest challenge in NA analysis based on prescription data is to differentiate between physician-induced and patient-induced medication changes. The first should be reflected in the adequate profile of an NA analysis and should not be misinterpreted as NA itself. The methodology described presents a powerful alternative for defining clinically meaningful prescription patterns.
Wilke T., Mueller S., Lindner R., Ahrens S., Verheyen F., A novel approach for Non-Adherence/Non-Persistence measurement based on prescription data: The example of oral diabetics in the therapy of type 2 diabetes mellitus patients, in: ISPOR 16th Annual International Meeting Research Abstracts May 21–25, 2011, Baltimore, MD, USA, Research Podium Abstracts, Research Poster Abstracts. .